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Precipitation Time Series Analysis and Forecasting for Italian Regions †.
- Source :
- Engineering Proceedings; 2023, Vol. 39, p23, 10p
- Publication Year :
- 2023
-
Abstract
- In Italy, most of the destructive landslides are triggered by rainfall, particularly in central Italy. Therefore, effective monitoring of rainfall is crucial in hazard management and ecosystem assessment. Global precipitation measurement (GPM) is the next-generation satellite mission, which provides the precipitation measurements worldwide. In this research, we employed the available monthly GPM data to estimate the monthly precipitation for the twenty administrative regions of Italy from June 2000 to June 2021. For each region, we applied the non-parametric Mann–Kendall test and its associated Sen's slope to estimate the precipitation trend for each calendar month. In addition, for each region, we estimated a linear trend and the seasonal cycles of precipitation with the antileakage least-squares spectral analysis (ALLSSA) and showed the annual precipitation variations using box plots. Lastly, we compared machine-learning models based on the auto-regressive moving average for monthly precipitation forecasting and showed that ALLSSA outperformed them. The findings of this research provide a significant insight into processing climate data, both in terms of trend-season estimates and forecasting, and can potentially be used in landslide susceptibility analysis. [ABSTRACT FROM AUTHOR]
- Subjects :
- LANDSLIDES
METEOROLOGICAL precipitation
REMOTE sensing
MACHINE learning
Subjects
Details
- Language :
- English
- ISSN :
- 26734591
- Volume :
- 39
- Database :
- Complementary Index
- Journal :
- Engineering Proceedings
- Publication Type :
- Academic Journal
- Accession number :
- 172047918
- Full Text :
- https://doi.org/10.3390/engproc2023039023